The use of artificial intelligence tools in data journalism: A content analysis of 7iber and ARIJ platforms
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Abstract
This study aims to conduct a content analysis of journalistic materials published by 7iber and ARIJ between 2022 and 2025, focusing on the extent to which artificial intelligence tools are used in data journalism. Addressing a research gap in Arab media contexts, the study adopts a qualitative content analysis methodology, utilizing a structured coding framework with categories including AI tool type, data type, presentation format, interactivity level, editorial purpose, and depth of data use. A purposive sample of ten articles (five from each platform) was selected based on relevance to data journalism and AI application. The results reveal that the most commonly used tools were text generation and data analytics, while more advanced tools—such as predictive modeling or interactive visualizations—remained underutilized. Most articles were presented in text-only formats and demonstrated low interactivity, indicating a gap between available technological capabilities and actual editorial implementation. Nevertheless, the limited interactivity found in this study remains a clear shortcoming, and aligns with prior critiques that AI tools are often underutilized in enabling immersive user experiences. The primary editorial purposes were found to be awareness, education, and investigation, and the most frequent level of data use was explanatory, rather than deep analytical engagement —with a majority of articles employing explanatory or descriptive approaches—suggest that AI is mainly supporting simplified storytelling rather than uncovering complex causal relationships or conducting exploratory analysis.
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